| 70 | log_print("Generated pickles!\n", "g") |
| 71 | |
| 72 | def get_from_folder(self, data_path, index): |
| 73 | |
| 74 | all_file_id = [] |
| 75 | pose_data = glob(data_path+'/*_pose.npy') |
| 76 | for file_name in pose_data: |
| 77 | all_file_id.append(file_name.split('_pose')[-2]) |
| 78 | all_file_id.sort() |
| 79 | all_data_df = pd.DataFrame(all_file_id, columns=["file"]) |
| 80 | all_data_df["pcd_position_x"] = all_data_df["file"].apply( |
| 81 | lambda x: np.load(x + '_pose.npy')[0]) |
| 82 | all_data_df["pcd_position_y"] = all_data_df["file"].apply( |
| 83 | lambda x: np.load(x + '_pose.npy')[1]) |
| 84 | all_data_df["pcd_position_z"] = all_data_df["file"].apply( |
| 85 | lambda x: np.load(x + '_pose.npy')[2]) |
| 86 | all_data_df["date"] = all_data_df["file"].apply( |
| 87 | lambda x: x.split('/')[-2]) |
| 88 | all_data_df.reset_index(drop=True, inplace=True) |
| 89 | return all_data_df |
| 90 | |
| 91 | def get_df(self, dataset_dir, type='train', is_shuffle=False): |
| 92 | file_df = pd.DataFrame() |